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一种在表面网络中生成动作电位和脑电图振荡的拓扑方法。

A topological method of generating action potentials and electroencephalography oscillations in a surface network.

作者信息

Sen Siddhartha

机构信息

Trinity College Dublin, Dublin, Ireland.

出版信息

R Soc Open Sci. 2025 May 28;12(5):241977. doi: 10.1098/rsos.241977. eCollection 2025 May.

DOI:10.1098/rsos.241977
PMID:40438545
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12115814/
Abstract

The brain is a source of continuous electrical activity, which includes one-dimensional voltage pulses (action potentials) that propagate along nerve fibres, transient localized oscillations and persistent surface oscillations in five distinct frequency bands. However, a unified theoretical framework for modelling these excitations is lacking. In this article, we provide such a framework by constructing a special surface network in which all observed brain-like signals, including surface oscillations, can be generated by topological means. Analytic expressions for all these excitations are found, and the values of the five frequency bands of surface oscillations are correctly predicted. It is shown how input signals of the system produce their own communication code to encode the information they carry and how the response output propagating signals produced carry this input information with them and can transfer it to the pathways they traverse as a non-transient topological memory structure of aligned spin-half protons. It is conjectured that the memory structure is located in the insulating sheaths of nerve fibres and is stable only if the pathways between the assembly of neurons, which represents a memory structure, include loops. The creation time and size of memory structures are estimated, and a memory-specific excitation frequency for a memory structure is identified and determined, which can be used to recall memories.

摘要

大脑是持续电活动的来源,这种电活动包括沿神经纤维传播的一维电压脉冲(动作电位)、短暂的局部振荡以及五个不同频段的持续表面振荡。然而,目前缺乏一个用于对这些激发进行建模的统一理论框架。在本文中,我们通过构建一个特殊的表面网络提供了这样一个框架,在该网络中,所有观察到的类似大脑的信号,包括表面振荡,都可以通过拓扑方式产生。我们找到了所有这些激发的解析表达式,并正确预测了表面振荡五个频段的值。文中展示了系统的输入信号如何产生自身的通信代码来编码它们所携带的信息,以及传播的响应输出信号如何携带此输入信息,并作为排列的自旋 - 1/2质子的非瞬态拓扑记忆结构将其传递到它们所经过的路径。据推测,记忆结构位于神经纤维的绝缘鞘中,并且只有当代表记忆结构的神经元集合之间的路径包含回路时才是稳定的。我们估计了记忆结构的创建时间和大小,并确定了记忆结构的特定记忆激发频率,该频率可用于回忆记忆。

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本文引用的文献

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Connectome-constrained networks predict neural activity across the fly visual system.连接组约束网络预测果蝇视觉系统中的神经活动。
Nature. 2024 Oct;634(8036):1132-1140. doi: 10.1038/s41586-024-07939-3. Epub 2024 Sep 11.
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Constructing the World from Inside Out: The brain probes your physical surroundings to select just the information needed to survive and flourish.由内而外构建世界:大脑探测你的物理环境,只为挑选出生存和繁荣所需的信息。
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If Engrams Are the Answer, What Is the Question?
如果“记忆印痕”是答案,那么问题是什么?
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Spindle-locked ripples mediate memory reactivation during human NREM sleep.纺锤波锁定位的尖峰涟漪介导人类非快速眼动睡眠中的记忆再激活。
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A coupled neural field model for the standard consolidation theory.一个用于标准固结理论的耦合神经场模型。
J Theor Biol. 2024 Jul 7;588:111818. doi: 10.1016/j.jtbi.2024.111818. Epub 2024 Apr 15.
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A design principle of spindle oscillations in mammalian sleep.哺乳动物睡眠中纺锤波振荡的一种设计原理。
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